NLP Training in York

NLP Training in York

Local, instructor-led live Natural Language Process (NLP) training courses demonstrate through interactive discussion and hands-on practice how to extract insights and meaning from this data. Utilizing different programming languages such as Python and R and Natural Language Processing (NLP) libraries, our trainings combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to help participants understand the meaning behind text data. NLP trainings walk participants step-by-step through the process of evaluating and applying the right algorithms to analyze data and report on its significance. NLP training is available as "onsite live training" or "remote live training". Onsite live training can be carried out locally on customer premises in York or in NobleProg corporate training centers in York. Remote live training is carried out by way of an interactive, remote desktop. NobleProg -- Your Local Training Provider

York - Priory Street Centre
Learn NLP in our training center in York. Accessible conference space centrally located in the heart of York,within easy walking distance from York railway station. Standard lunch is a mixture of vegetarian and non-vegetarian food, which can be tailored to individual requirements and we can offer catering for a wide range of specialist dietary, cultural or religious needs. Where possible, we ask our suppliers to source fair trade or local produce that is organic, free range and GM free. Address: 15 Priory Street, York, YO1 6ET... Read more

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NLP Subcategories

NLP Course Events - York

CodeNameVenueDurationCourse DateCourse Price [Remote / Classroom]
python_nltkNatural Language Processing with PythonYork - Priory Street Centre 28 hoursTue, 2018-10-09 09:30£5200 / £5800
nlpNatural Language ProcessingYork - Priory Street Centre 21 hoursTue, 2018-10-16 09:30£3900 / £4350
pythontextmlPython: Machine Learning with TextYork - Priory Street Centre 21 hoursWed, 2018-10-17 09:30£3900 / £4350
aiintArtificial Intelligence OverviewYork - Priory Street Centre 7 hoursTue, 2018-10-23 09:30£1300 / £1450
nlpwithrNLP: Natural Language Processing with RYork - Priory Street Centre 21 hoursWed, 2018-10-24 09:30£3900 / £4350
opennlpOpenNLP for Text Based Machine LearningYork - Priory Street Centre 14 hoursThu, 2018-10-25 09:30£2600 / £2900
textsumText Summarization with PythonYork - Priory Street Centre 14 hoursMon, 2018-10-29 09:30£2200 / £2500
w2vdl4jNLP with Deeplearning4jYork - Priory Street Centre 14 hoursTue, 2018-10-30 09:30£2600 / £2900
nlgPython for Natural Language GenerationYork - Priory Street Centre 21 hoursWed, 2018-10-31 09:30£3900 / £4350
dlfornlpDeep Learning for NLP (Natural Language Processing)York - Priory Street Centre 28 hoursMon, 2018-11-12 09:30£5200 / £5800
python_nlpNatural Language Processing with Deep Dive in Python and NLTKYork - Priory Street Centre 35 hoursMon, 2018-11-12 09:30£6500 / £7250
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLPYork - Priory Street Centre 21 hoursWed, 2018-11-14 09:30£3900 / £4350
NPL_LBGNatural Language Processing - AI/RoboticsYork - Priory Street Centre 21 hoursWed, 2018-11-14 09:30£3900 / £4350
tsflw2vNatural Language Processing with TensorFlowYork - Priory Street Centre 35 hoursMon, 2018-11-19 09:30£6500 / £7250
chatbotpythonBuilding Chatbots in PythonYork - Priory Street Centre 21 hoursWed, 2018-11-21 09:30£3300 / £3750
mldlnlpintroML、DL與NLP入門與進階大綱York - Priory Street Centre 14 hoursThu, 2018-11-22 09:30£2200 / £2500
python_nltkNatural Language Processing with PythonYork - Priory Street Centre 28 hoursMon, 2018-12-03 09:30£5200 / £5800
nlpNatural Language ProcessingYork - Priory Street Centre 21 hoursMon, 2018-12-10 09:30£3900 / £4350
pythontextmlPython: Machine Learning with TextYork - Priory Street Centre 21 hoursTue, 2018-12-11 09:30£3900 / £4350
aiintArtificial Intelligence OverviewYork - Priory Street Centre 7 hoursMon, 2018-12-17 09:30£1300 / £1450
nlpwithrNLP: Natural Language Processing with RYork - Priory Street Centre 21 hoursWed, 2018-12-19 09:30£3900 / £4350
opennlpOpenNLP for Text Based Machine LearningYork - Priory Street Centre 14 hoursWed, 2018-12-26 09:30£2600 / £2900
w2vdl4jNLP with Deeplearning4jYork - Priory Street Centre 14 hoursWed, 2018-12-26 09:30£2600 / £2900
nlgPython for Natural Language GenerationYork - Priory Street Centre 21 hoursWed, 2018-12-26 09:30£3900 / £4350
textsumText Summarization with PythonYork - Priory Street Centre 14 hoursTue, 2019-01-01 09:30£2200 / £2500
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLPYork - Priory Street Centre 21 hoursMon, 2019-01-07 09:30£3900 / £4350
NPL_LBGNatural Language Processing - AI/RoboticsYork - Priory Street Centre 21 hoursTue, 2019-01-08 09:30£3900 / £4350
dlfornlpDeep Learning for NLP (Natural Language Processing)York - Priory Street Centre 28 hoursMon, 2019-01-14 09:30£5200 / £5800
chatbotpythonBuilding Chatbots in PythonYork - Priory Street Centre 21 hoursMon, 2019-01-14 09:30£3300 / £3750
tsflw2vNatural Language Processing with TensorFlowYork - Priory Street Centre 35 hoursMon, 2019-01-21 09:30£6500 / £7250

NLP Course Outlines in York

CodeNameDurationOverview
aiintArtificial Intelligence Overview7 hoursThis course has been created for managers, solutions architects, innovation officers, CTOs, software architects and anyone who is interested in an overview of applied artificial intelligence and the nearest forecast for its development.
nlpNatural Language Processing21 hoursThis course has been designed for people interested in extracting meaning from written English text, though the knowledge can be applied to other human languages as well.

The course will cover how to make use of text written by humans, such as blog posts, tweets, etc...

For example, an analyst can set up an algorithm which will reach a conclusion automatically based on extensive data source.
python_nltkNatural Language Processing with Python28 hoursThis course introduces linguists or programmers to NLP in Python. During this course we will mostly use nltk.org (Natural Language Tool Kit), but also we will use other libraries relevant and useful for NLP. At the moment we can conduct this course in Python 2.x or Python 3.x. Examples are in English or Mandarin (普通话). Other languages can be also made available if agreed before booking.
tsflw2vNatural Language Processing with TensorFlow35 hoursTensorFlow™ is an open source software library for numerical computation using data flow graphs.

SyntaxNet is a neural-network Natural Language Processing framework for TensorFlow.

Word2Vec is used for learning vector representations of words, called "word embeddings". Word2vec is a particularly computationally-efficient predictive model for learning word embeddings from raw text. It comes in two flavors, the Continuous Bag-of-Words model (CBOW) and the Skip-Gram model (Chapter 3.1 and 3.2 in Mikolov et al.).

Used in tandem, SyntaxNet and Word2Vec allows users to generate Learned Embedding models from Natural Language input.

Audience

This course is targeted at Developers and engineers who intend to work with SyntaxNet and Word2Vec models in their TensorFlow graphs.

After completing this course, delegates will:

- understand TensorFlow’s structure and deployment mechanisms
- be able to carry out installation / production environment / architecture tasks and configuration
- be able to assess code quality, perform debugging, monitoring
- be able to implement advanced production like training models, embedding terms, building graphs and logging
w2vdl4jNLP with Deeplearning4j14 hoursDeeplearning4j is an open-source, distributed deep-learning library written for Java and Scala. Integrated with Hadoop and Spark, DL4J is designed to be used in business environments on distributed GPUs and CPUs.

Word2Vec is a method of computing vector representations of words introduced by a team of researchers at Google led by Tomas Mikolov.

Audience

This course is directed at researchers, engineers and developers seeking to utilize Deeplearning4J to construct Word2Vec models.
aitechArtificial Intelligence - the most applied stuff - Data Analysis + Distributed AI + NLP21 hoursThis course is aimed at developers and data scientists who wish to understand and implement AI within their applications. Special focus is given to Data Analysis, Distributed AI and NLP.
nlpwithrNLP: Natural Language Processing with R21 hoursIt is estimated that unstructured data accounts for more than 90 percent of all data, much of it in the form of text. Blog posts, tweets, social media, and other digital publications continuously add to this growing body of data.

This course centers around extracting insights and meaning from this data. Utilizing the R Language and Natural Language Processing (NLP) libraries, we combine concepts and techniques from computer science, artificial intelligence, and computational linguistics to algorithmically understand the meaning behind text data. Data samples are available in various languages per customer requirements.

By the end of this training participants will be able to prepare data sets (large and small) from disparate sources, then apply the right algorithms to analyze and report on its significance.

Audience
Linguists and programmers

Format of the course
Part lecture, part discussion, heavy hands-on practice, occasional tests to gauge understanding
mldlnlpintroML、DL與NLP入門與進階大綱14 hoursThe aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the Python programming language and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.

Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.
pythontextmlPython: Machine Learning with Text21 hoursIn this instructor-led, live training, participants will learn how to use the right machine learning and NLP (Natural Language Processing) techniques to extract value from text-based data.

By the end of this training, participants will be able to:

- Solve text-based data science problems with high-quality, reusable code
- Apply different aspects of scikit-learn (classification, clustering, regression, dimensionality reduction) to solve problems
- Build effective machine learning models using text-based data
- Create a dataset and extract features from unstructured text
- Visualize data with Matplotlib
- Build and evaluate models to gain insight
- Troubleshoot text encoding errors

Audience

- Developers
- Data Scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
nlgPython for Natural Language Generation21 hoursNatural language generation (NLG) refers to the production of natural language text or speech by a computer.

In this instructor-led, live training, participants will learn how to use Python to produce high-quality natural language text by building their own NLG system from scratch. Case studies will also be examined and the relevant concepts will be applied to live lab projects for generating content.

By the end of this training, participants will be able to:

- Use NLG to automatically generate content for various industries, from journalism, to real estate, to weather and sports reporting
- Select and organize source content, plan sentences, and prepare a system for automatic generation of original content
- Understand the NLG pipeline and apply the right techniques at each stage
- Understand the architecture of a Natural Language Generation (NLG) system
- Implement the most suitable algorithms and models for analysis and ordering
- Pull data from publicly available data sources as well as curated databases to use as material for generated text
- Replace manual and laborious writing processes with computer-generated, automated content creation

Audience

- Developers
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
python_nlpNatural Language Processing with Deep Dive in Python and NLTK35 hoursBy the end of the training the delegates are expected to be sufficiently equipped with the essential python concepts and should be able to sufficiently use NLTK to implement most of the NLP and ML based operations. The training is aimed at giving not just an executional knowledge but also the logical and operational knowledge of the technology therein.
opennlpOpenNLP for Text Based Machine Learning14 hoursThe Apache OpenNLP library is a machine learning based toolkit for processing natural language text. It supports the most common NLP tasks, such as language detection, tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, parsing and coreference resolution.

In this instructor-led, live training, participants will learn how to create models for processing text based data using OpenNLP. Sample training data as well customized data sets will be used as the basis for the lab exercises.

By the end of this training, participants will be able to:

- Install and configure OpenNLP
- Download existing models as well as create their own
- Train the models on various sets of sample data
- Integrate OpenNLP with existing Java applications

Audience

- Developers
- Data scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
textsumText Summarization with Python14 hoursIn Python Machine Learning, the Text Summarization feature is able to read the input text and produce a text summary. This capability is available from the command-line or as a Python API/Library. One exciting application is the rapid creation of executive summaries; this is particularly useful for organizations that need to review large bodies of text data before generating reports and presentations.

In this instructor-led, live training, participants will learn to use Python to create a simple application that auto-generates a summary of input text.

By the end of this training, participants will be able to:

- Use a command-line tool that summarizes text.
- Design and create Text Summarization code using Python libraries.
- Evaluate three Python summarization libraries: sumy 0.7.0, pysummarization 1.0.4, readless 1.0.17

Audience

- Developers
- Data Scientists

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
dlfornlpDeep Learning for NLP (Natural Language Processing)28 hoursDeep Learning for NLP allows a machine to learn simple to complex language processing. Among the tasks currently possible are language translation and caption generation for photos. DL (Deep Learning) is a subset of ML (Machine Learning). Python is a popular programming language that contains libraries for Deep Learning for NLP.

In this instructor-led, live training, participants will learn to use Python libraries for NLP (Natural Language Processing) as they create an application that processes a set of pictures and generates captions.

By the end of this training, participants will be able to:

- Design and code DL for NLP using Python libraries
- Create Python code that reads a substantially huge collection of pictures and generates keywords
- Create Python Code that generates captions from the detected keywords

Audience

- Programmers with interest in linguistics
- Programmers who seek an understanding of NLP (Natural Language Processing)

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice
NPL_LBGNatural Language Processing - AI/Robotics21 hoursThis classroom based training session will explore NLP techniques in conjunction with the application of AI and Robotics in business. Delegates will undertake computer based examples and case study solving exercises using Python
chatbotpythonBuilding Chatbots in Python21 hoursChatBots are computer programs that automatically simulate human responses via chat interfaces. ChatBots help organizations maximize their operations efficiency by providing easier and faster options for their user interactions.

In this instructor-led, live training, participants will learn how to build chatbots in Python.

By the end of this training, participants will be able to:

- Understand the fundamentals of building chatbots
- Build, test, deploy, and troubleshoot various chatbots using Python

Audience

- Developers

Format of the course

- Part lecture, part discussion, exercises and heavy hands-on practice

Note

- To request a customized training for this course, please contact us to arrange.
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Course Discounts

Course Venue Course Date Course Price [Remote / Classroom]
Selenium WebDriver in C#: Introduction to Web Testing Automation in C# Sheffield Wed, 2018-09-26 09:30 £2178 / £2578
Introduction to Ansible Automation London, Hatton Garden Mon, 2018-10-08 09:30 £1089 / £1464
Jenkins: Continuous Integration for Agile Development Manchester, King Street Thu, 2018-10-18 09:30 £2574 / £3224
Introduction to Recommendation Systems Swansea- Princess House Thu, 2018-10-18 09:30 £990 / £1140
Impact Evaluation – Quantitative Analysis London, Hatton Garden Wed, 2018-10-24 09:30 £2574 / £3324
CakePHP: Rapid Web Application Development Birmingham Tue, 2018-11-06 09:30 £4356 / £5656

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